Predation affects body shape in the knife livebearer Alfaro cultratus (Cyprinodontiformes: Poeciliidae)

Abstract Livebearing fishes are a common model for studying the effects of predation on prey biology. Numerous studies have found differences in life history, sexual selection, behavior, and morphology between populations of the same species that co‐occur with predators and those that do not. Alfaro cultratus is a livebearing fish with populations in different predation environments, but unlike other livebearers, this species also has an extreme body shape that is laterally compressed. Given this unusual morphology, we asked if predation environment would still predict overall body shape, as has been documented in other species. We collected specimens from both predator and no predator sites in Costa Rica and used a geometric morphometrics analysis to determine if body shape is affected by predation environment, while controlling for size and river gradient. Body shape does indeed differ between predation environments; however, the observed differences contrast with the patterns found in other livebearer systems. Alfaro cultratus in predation environments had deeper and shorter bodies and deeper caudal peduncles than those found in environments without dominant fish predators.

. In general, fish from predator populations exhibit a larger caudal region, smaller head, more elongated body, and posterior-ventral eye position relative to predator-free populations (Langerhans et al., 2004).Later studies showed that these patterns hold in other species across the family (Ingley et al., 2014;Langerhans & DeWitt, 2004;Langerhans & Makowicz, 2009), suggesting a pattern of converging evolutionary divergence among populations and species.
However, more recent studies show that body shape is a complex trait that responds simultaneously to more than one selective pressure, often reflecting a trade-off between optimal shapes for different pressures (Burns et al., 2009;Williams et al., 2017).In low predation systems, competition is the more important selective agent, but when a predator is present, avoiding predation becomes the most important pressure (Langerhans, 2009).In Brachyrhaphis rhabdophora, body shape differs between predator and non-predator populations, but pregnant females tend to converge on a common shape, demonstrating a trade-off between reproduction and optimal shape for survival (Wesner et al., 2011).These data suggest predation is important to the evolution of fish body shape, but most of the studies on variation in body shape as affected by predation environment are limited to a relatively small number of taxa with a typical round-bodied (in cross section) form (Ingley et al., 2014;Langerhans & DeWitt, 2004;Langerhans & Makowicz, 2009).Unfortunately, we know almost nothing about fishes that have narrow-bodied shape, which might have evolved as a response to selective pressures other than predation and may not fit the standard expected morphological predictions (Belk et al., 2011).What is needed are systems that allow us to examine effects of predation environment on body shape in fishes with more extreme body forms.
Alfaro cultratus presents a good system for evaluating the effect of predation on body shape in a poecilid with an atypical morphology.This species is highly laterally compressed with the lower margin of the caudal peduncle sharpened with scales forming a keel; thus, the common name knife livebearer (Bussing, 2002).Interestingly, both males and females have this body shape, and females maintain it during pregnancy (Wesner et al., 2011).Populations inhabiting the Atlantic versant of Costa Rica include systems with the presence of piscivorous predators including Parachromis dovii, and P. managuensis (high predation environment), and systems with few or no predators (low predation environment).Body shape response to predation across both types of environments might be analogous to that found in other livebearer systems (Ingley et al., 2014;Langerhans & DeWitt, 2004;Langerhans & Makowicz, 2009), it might show differences in body shape that are not analogous to other livebearer systems due to the interaction of predation with other selective pressures or there might be no differences in body shape between predation environments.For example, little variation in life history traits in A. cultratus was found between high and low predation environments (Golden et al., 2021), a contrast to the life history pattern found in other livebearer species (Johnson & Belk, 2001;Johnson & Zúñiga-Vega, 2009;Reznick & Travis, 2019).This absence of divergence in life history between predation environments can be attributed to a limitation imposed by the compressed body shape of A. cultratus.This adaptation to a high velocity environment could in turn hinder the divergence in response to life history variations even in the presence of differing predation pressures among populations (Golden et al., 2021).A corollary implication is that body shape might remain consistent across predation environments due to the shared constraint from having a body adapted to high-velocity environments.
Here, we tested whether body shape in A. cultratus diverges in response to predation environment and if that divergence is consistent with what has been reported for other livebearer species (Belk et al., 2020;Ingley et al., 2014;Langerhans et al., 2004;Langerhans & DeWitt, 2004) in spite of its atypical shape.Specifically, we test if, in the presence of predators, fish had a larger caudal region, smaller head, more elongate body, and posterior-ventral eye position, relative to fish from predator-free environments.

| Study site and collection
We collected A. cultratus individuals from 16 different sites in Costa Rica (see Figure 1 and Table 1) using a handheld seine (1.3 × 5 m; 8 mm mesh size), attempting to collect approximately 100 females for a life history study (Golden et al., 2021), a good proportion of which were adults used in the present study (see Table 1 for sample sizes for each sampling location).We categorized five of these locations as low predation environments (i.e., no piscivorous fishes were present) and 11 locations as high predation environments in a binary way, analogous to the classic Trinidadian guppy system (Reznick & Endler, 1982).We defined predation environments as "high predation environments" if we caught or observed either or both P. dovii or Parachromis managuensis (Bussing, 2002) during the sampling for A. cultratus specimens, and as "low predation environments" if we did not.Ten or more seine hauls were carried out at each location.We designated both site types as "high" or "low predation environments" but acknowledge that predation risk may be confounded with other environmental factors like resource availability, elevation, temperature, river flow, and density and that presence of predators may be causally or incidentally correlated to these or other factors (Johnson, 2002;Jourdan et al., 2016).Other forms of predation on fishes likely exist at these sites, including bird and invertebrate predation, but we did not account for their presence and densities in this study.Although some researchers have highlighted that predation should be studied as a gradient that considers temporal and spatial variation in predation risk (Deacon et al., 2018), classifying localities in a binary way has been shown to accurately predict mortality rates and divergent life history traits in the Costa Rican livebearer B. rhabdophora (Johnson, 2002;Johnson & Belk, 2001;Johnson & Zúñiga-Vega, 2009), so although we did not measure mortality directly, we are using presence and absence of known fish predators as a predictor of mortality.We also calculated stream gradient at each location and used this factor as a covariate in our analyses (see below).The stream gradient was calculated using geographic information systems to calculate the difference in elevation (in m) over 1000 m stream length (500 m upstream and 500 m downstream of the collection site).The difference in elevation was divided by 1000 m and multiplied by 100 to obtain percent gradient.
We consider gradient to be a predictor of river flow velocity, a factor associated with body shape in other fish species (Haas et al., 2015;Mercer, 2020).Low predation sites ranged in gradient from 2.29% to 7.75% and high predation sites from 3.02% to 6.14%.
All fish were collected in April 2019 under Brigham Young University Institutional Animal Care and Use Committee approval (protocol #15-0404).We conducted this work with permission from the Vida Silvestre, Sistema Nacional de Áreas de Conservación in Costa Rica (R-SINAC-PNI-ACAHN-011-2019).We euthanized collected specimens in the field with an overdose of 3-amenobenzoic acid ethyl ester (MS-222) and then preserved them in 95% ethyl alcohol.Once transported to the laboratory, we stored specimens in 70% ethanol.We then measured and photographed each fish on the left side using an Apple iPad.We accessioned specimens into the Monte L. Bean Life Science Museum fish collections at Brigham Young University in Provo, Utah, USA.

| Geometric morphometrics
We used 459 female specimens of A. cultratus for our analysis.
Because A. cultratus is sexually dimorphic, we excluded males from the analysis.We photographed all specimens on their left side and digitized 11 landmarks to characterize body shape (Figure 2), using the software tpsDig (Rohlf, 2003a) effect of location).This procedure results in reduced digitization error and a random distribution of error compared to multiple individuals digitizing separate parts (i.e., locations or groups) of the data (Moccetti et al., 2023).
We used the software tpsRelW to align the specimens using a generalized Procrustes analysis to remove nonshape variation (Rohlf, 2015;Rohlf & Slice, 1990) and to generate shape variables for the images (Rohlf, 2003c).Shape variables were initially generated as partial warps and uniform components (W or weight matrix).
The program then runs a principal component analysis of the weight matrix to generate relative warps to use as our measure for shape analysis.Relative warps are linear combinations of uniform and nonuniform shape components that are orthogonal to each other (Zelditch et al., 2012), and they capture multivariate shape variation in fewer dimensions.We used the first 12 relative warps (explaining 98% of shape variation) as response variables.This dimension reduction is important because of the use of sliding semi-landmarks in the landmarking scheme.Landmarks carry two degrees of freedom, but sliding semi-landmarks only have one true degree of freedom; thus, including all shape variables included in the original weight matrix creates far more degrees of freedom than are available in the data.Furthermore, we typically remove relative warps that individually account for <1% of shape variation.This reduction improves the likelihood of convergence for the parametric model (multivariate linear mixed model), and, again, guards against the inflation of degrees of freedom that individually account for none, or only a small amount, of the total shape variation.

| Statistical analysis
We used a multivariate linear mixed model to determine the effects of predator environment on shape variation in A. cultratus.The response variable was shape as characterized by the first 12 relative warps.The predictor variables were predation environment, stream gradient (covariate), centroid size (covariate), and an index variable to account for the order of the relative warps and all two-way interactions between predictors and the index variable.Size and gradient are known to affect body shape (Haas et al., 2015;Hassell et al., 2012;Langerhans, 2008;Meyer, 1990;Williams et al., 2017) in fishes, and although our samples exhibit little variation in both, we used centroid size (a multivariate measure of size) for each specimen and the gradient of the site as covariates.We specifically wanted to test for an effect of predation on body shape after adjusting for possible effects of body size (i.e., centroid size) and stream gradient (i.e., water velocity).Collection location was treated as a random effect, hence creating the need for a multivariate (multiple shape variables analyzed simultaneously) mixed (fixed and random effects) model.
A mixed-model framework assumes a univariate response variable, so we vectorized the shape variables such that each row F I G U R E 2 Photograph of Alfaro cultratus specimen with position of landmarks in red and semilandmarks in blue along the body.
represented one response variable, but each specimen was represented by multiple rows of data (Anderson, 2003).Thus, the first row represented relative warp 1 for the first specimen, the second row represented relative warp 2 for the first specimen, and so forth until all relative warps were represented in successive rows for the first individual.The same pattern was repeated for all individuals, each with 12 rows.The index variable preserved the order of the relative warps such that comparisons between groups (e.g., high predation/low predation) were made by matching each relative warp to the same relative warp in each group (i.e., relative warp 1 in the high predation environment was compared to relative warp 1 in the low predation environment).Our main goal was to determine how predation environment affects body shape; thus, it is the two-way interaction of the predation environment and the index variable that tested the hypothesis of interest (i.e., does shape vary on at least some of the relative warps between predation environments).
Main effects by themselves test only for an average effect across all relative warps.Because relative warps are principal components, they have a mean of 0; and more importantly, they have an arbitrary ordination.Thus, a single individual may have a positive score on some relative warps and a negative score on other relative warps so that their mean score across all relative warps may be near 0. It was only by matching relative warps in the same order (by using the index variable as a predictor) that we could accurately test the hypothesis of interest (Hassell et al., 2012;Ingley et al., 2014;Roth-Monzón et al., 2020;Searle et al., 2021;Wesner et al., 2011).We estimated degrees of freedom using the Kenward and Roger method (1997).
We used Proc MIXED in SAS to run this analysis (SAS version 9.4; SAS Institute Inc., Cary, NC, USA).
To visualize the effects of predation environment on shape, we calculated a divergence vector (Langerhans, 2009;Langerhans & Makowicz, 2009) that characterizes differences in shape across all relative warps for discrete predictor variables.We calculated this divergence vector by summing the products of the first eigenvector (from a principal components analysis of the least squares means for each relative warp in the two predation environments) multiplied by the associated relative warp scores for each fish.We then regressed divergence scores for each individual on their respective shape variables in tpsRegr (Rohlf, 2003b) to generate thin-plate spline visualizations of the extremes of shape variation between predation environments.Resulting thin-plate splines represent shape divergence across all relative warps between predation environments.

| RE SULTS
Predation environment had a significant effect on body shape as indicated by the significant interaction with the index variable (Table 2).The covariates stream gradient and centroid size each also accounted for significant variation in body shape (Table 2).Relative warps 1, 2, 3, 5, 8, and 10 showed significant differences between high predation and low predation environments (Figure 3).Fish in Relative warp number

Low predation
High predation 10 high predation environments exhibited deeper and shorter bodies and a deeper but shorter caudal peduncle area relative to those in low predation environments.In addition, fish in high predation environments had relatively larger heads and a longer rostrum, and the eye shifted more posterior and dorsal compared to fish in low predation environments (Figure 4).

| DISCUSS ION
Body shape in female A. cultratus differs significantly between high and low predation environments.However, the way in which shape differs between predation environments is not consistent with patterns found in other fish and specifically livebearing fish systems.Typically, livebearers from high predation environments exhibit a relatively more elongate body, longer and deeper caudal peduncle, shallower anterior head or body region, and a lower eye position than fish in the same species from low predation sites (Ingley et al., 2014;Langerhans, 2009;Langerhans & DeWitt, 2004;Langerhans & Makowicz, 2009).The deeper caudal peduncle is considered an adaptation for predator avoidance, and it has been shown in experimental studies to result in faster burst-swimming (Langerhans et al., 2004).The slab-sided body shape of A. cultratus appears to be a hydrodynamic adaptation for stabilized swimming because it reduces turbulence and thus energetic costs (Araújo et al., 2017;Belk et al., 2011;Golden et al., 2021) when swimming in high velocities.At sites where A. cultratus co-occurs with predators, we also observed enlargement of the caudal peduncle but without the accompanying elongated body.Instead, our sample showed a shortening of the body along with deepening of the head and a more dorsal eye position, in the presence of predators.We hypothesize that this shape combination is due to the interaction between adaptations for steady swimming at high river currents and predator avoidance.
This type of morphological shift in response to predators has not been well explored in other systems.Deepening of the body has been proposed as an adaptation to avoid predation from gapelimited piscivores that eat prey whole and by increasing handling time that provides greater opportunity for escape (Belk & Hales Jr, 1993;Brönmark & Miner, 1992;Portz & Tyus, 2004;Williams et al., 2017).The increase in the anterior body depth of A. cultratus may function as an antipredator adaptation against the relatively small predators that inhabit the small streams where this species occurs.The distribution of body sizes of prey and gape sizes of predators would be a fruitful area for future research to determine if gape limitation is important in these systems.
Although the effect of predation on life history is a consequence of differential mortality among age or size classes (Johnson & Bagley, 2011), predation affects body shape by giving selective advantages to those individuals whose morphologies allow them to evade predation either by avoiding predation by gape size limited predators, improving burst speed, or having better predator detection.Among the populations included in this study, A. cultratus exhibits no differences in life history traits (Golden et al., 2021).This lack of difference in life history traits is strikingly different from patterns found in other poecilid species (Downhower et al., 2000;Golden et al., 2021;Jennions et al., 2006;Johnson & Bagley, 2011;Johnson & Belk, 2001;Reznick & Endler, 1982).Lack of response to predation in life history traits was hypothesized to be due to a shape constraint preventing the divergence because of the species having evolved a narrow body and ventral keel that might be selected for efficient swimming in the environments they live in regardless of predation (Golden et al., 2021).The morphometric results further support the constraint hypothesis by suggesting that predation does have an effect in the species, but that the constraint for efficient swimming might be causing shape in A. cultratus to differ in a nontypical way between predation environments.These results seem to indicate that life history is more restrained than morphology in narrow-bodied species.Piscivores in this system might not be exerting preferential mortality on a specific size class (Johnson & Bagley, 2011), but they may be selectively consuming shallow-bodied individuals that fit within their gape.This sort of selection by predators could lead to the patterns in body shape observed here.In addition, gape-limited predation can result in differences in size among populations, and as noted above size can be related to life history variation among populations.However, in this study, the range of individual length for each sample is highly overlapping between predator and non-predator locations (Table 1), and in a previous study, there was no difference in mean size at maturity between predator and non-predator sites for both males and females (Golden et al., 2021), suggesting that differences in shape are not a consequence of differences in size among locations.Gape-limited predation, as we have discussed it here, relates mainly to piscivorous fishes.In contrast, the presence and densities F I G U R E 4 Thin-plate splines representing the extremes of body shape variation in response to predation environment.
of birds or invertebrate predators and their effects on body shape of fishes might represent an important effect for future consideration that has not been well studied yet.
The selective pressures behind the ventral keel and unusual shape of female A. cultratus are still not fully understood.Whether such patterns hold in males also presents an interesting question.
The suggestion that this shape contributes to better stabilized swimming needs to be experimentally tested, and differences in performance in both steady swimming and burst swimming between low and high predation environment populations need to be compared to determine whether the differences in body shape observed in this study provide any sort of antipredator advantage.

CO N FLI C T O F I NTE R E S T S TATE M E NT
None declared.
. Landmarks were (1) tip of the snout; (2) posterior extent of the operculum projected onto the dorsal outline; (3) anterior insertion of the dorsal fin; (4) dorsal insertion of the caudal fin; (5) ventral insertion of the caudal fin; (6) anterior insertion of the anal fin; (7) front of the eye; (8) back of the eye; (9) semilandmark on the dorsal outline halfway between landmarks 2 and 3; (10) semilandmark on the ventral outline at 2/3 the distance between landmarks 1 and 6; and (11) semilandmark on the ventral outline halfway between landmarks 5 and 6.A single person was responsible for digitizing all specimens, and digitizing was carried out without reference to the predictor variables (including the random F I G U R E 1 Collection locations in Costa Rica for high and low predation populations of Alfaro cultratus. Data curation (supporting); formal analysis (equal); visualization (lead); writing -original draft (lead); writing -review and editing (lead).Kaitlyn B. Golden: Data curation (lead); investigation (lead); writing -review and editing (equal).Trevor J. Williams: Investigation (supporting); writing -review and editing (equal).Mark C. Belk: Conceptualization (equal); formal analysis (equal); methodology (lead); supervision (equal); writing -review and editing (equal).Jerald B. Johnson: Conceptualization (equal); supervision (equal); writing -review and editing (equal).ACK N O WLE D G E M ENTSThis work was supported by the Department of Biology and Graduate Studies at Brigham Young State University.We are grateful to the staff at the Sistema Nacional de Áreas de Conservación (SINAC) who assisted us with the collection permits.Professor Thomas Quinn at the University of Washington for providing laboratory space and equipment to KBG for photographing specimens while in Seattle.Matthew Rowley from BYU's Geospatial Services and Training for his assistance with gradient calculations for the analysis.

TA B L E 1
Locality information.
Multivariate analysis of covariance effects for body shape (type 3 table).
TA B L E 2